Essays about: "deep multi-agent reinforcement learning"
Showing result 11 - 15 of 21 essays containing the words deep multi-agent reinforcement learning.
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11. Multi Agent Reinforcement Learning for Game Theory : Financial Graphs
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : We present the rich research potential at the union of multi agent reinforcement learning (MARL), game theory, and financial graphs. We demonstrate how multiple game theoretic scenarios arise in three node financial graphs with minor modifications. We highlight six scenarios used in this study. READ MORE
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12. MULTI-AGENT REINFORCEMENT LEARNING WITH APPLICATION ON TRAFFIC FLOW CONTROL
University essay from Uppsala universitet/Statistiska institutionenAbstract : Traffic congestion diminish driving experience and increases the CO2 emissions. With the rise of 5G and machine learning, the possibilities to reduce traffic congestion are endless. This thesis aims to study if multi-agent reinforcement learning speed recommendations on a vehicle level can reduce congestion and thus control traffic flow. READ MORE
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13. Distributed Deep Reinforcement Learning for a Multi-Robot Warehouse System
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This project concerns optimizing the behavior ofmultiple dispatching robots in a virtual warehouse environment.Q-learning and deep Q-learning algorithms, two establishedmethods in reinforcement learning, were used for this purpose. READ MORE
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14. Distributed Optimization Through Deep Reinforcement Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Reinforcement learning methods allows self-learningagents to play video- and board games autonomously. Thisproject aims to study the efficiency of the reinforcement learningalgorithms Q-learning and deep Q-learning for dynamical multi-agent problems. The goal is to train robots to optimally navigatethrough a warehouse without colliding. READ MORE
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15. Tacit collusion with deep multi-agent reinforcement learning
University essay from Handelshögskolan i Stockholm/Institutionen för nationalekonomiAbstract : Automatic pricing now attracts the attention of competition authorities following recent machine learning developments. In particular, previous research shows that the Q-learning algorithm can reach collusive outcomes despite receiving only minimal human intervention. READ MORE